焊接机器人智能控制程序的研究与实现
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摘要
焊接机器人机械臂的轨迹规划在工业机器人的智能控制中具有重要的地位。传统的机械臂焊接方法采用的是示教-再现方式,一次示教,整个工作流程都遵循示教的流程进行焊接,这种一成不变的焊接模式难以达到工业领域高效率、低耗能的要求,而通过人工优化焊接轨迹又存在优化困难并难于实现自动控制。因此,让焊接机器人机械臂在反复执行相同任务的过程中,通过智能算法,寻求一条效率更高、代价更低,乃至最优的轨迹规划成为焊接机器人领域智能控制的研究重点。
本论文通过系统能量和时间优化两个方面,对机械臂焊接芯片的路径进行优化。系统能量方面,应用Denavit-Hartenberg理论进行关节坐标和笛卡尔坐标的转换,建立运动方程,通过设置满足工业需求的规则有效地实现机械手轨迹规划自学习的能力；时间优化方面,研究芯片焊点的分布,把问题转换成哈密尔顿回路求解问题,应用改进的遗传算法求得优化的哈密尔顿回路,使机械臂焊接路径得到优化,实验结果表明了改进的遗传算法在机械手焊接芯片实际应用的有效性。
Welding robot manipulator trajectory planning for industrial robots intelligent control has an important position.The trajectory planning of welding robot manipulator occupy an important position in the intelligent control of industrial robots.The traditional method used by welding manipulator is teaching-reproduction, once teached, the entire workflow process will follow it to weld, while such static model hardly achieve the high efficiency, low power requirements of industrial welding, on the other hand, manual optimization of welding trajectory is very difficult and hard to get this under automatic control. For this reason, in the process of welding robot manipulator repeatedly perform the same tasks, how to find a more efficient, less costly, and even the optimal trajectory through smart algorithms is the key point in the field of intelligent control of welding robot.
In this thesis, the chip welding trajectory of manipulator was optimised from both the system energy and time. In the aspect of system energy, the Denavit-Hartenberg theory was used to achieve joint coordinates and Cartesian coordinate transformation, establish the motion equations, so to obtain effective self-learning capabilities of welding robot manipulator trajectory planning by setting some rules to meet the industry needs. In the aspect of time optimization, through the research of chip solder joints' distribution, the problem was transformed to the Hamilton circuit problem, improved genetic algorithm was used to obtaind optimal Hamilton circuit, so to optimise manipulator's welding trajectory. The effectiveness of improved genetic algorithm in the practical application of manipulator's chip welding was proved by the result of experiments.
本论文通过系统能量和时间优化两个方面,对机械臂焊接芯片的路径进行优化。系统能量方面,应用Denavit-Hartenberg理论进行关节坐标和笛卡尔坐标的转换,建立运动方程,通过设置满足工业需求的规则有效地实现机械手轨迹规划自学习的能力；时间优化方面,研究芯片焊点的分布,把问题转换成哈密尔顿回路求解问题,应用改进的遗传算法求得优化的哈密尔顿回路,使机械臂焊接路径得到优化,实验结果表明了改进的遗传算法在机械手焊接芯片实际应用的有效性。
Welding robot manipulator trajectory planning for industrial robots intelligent control has an important position.The trajectory planning of welding robot manipulator occupy an important position in the intelligent control of industrial robots.The traditional method used by welding manipulator is teaching-reproduction, once teached, the entire workflow process will follow it to weld, while such static model hardly achieve the high efficiency, low power requirements of industrial welding, on the other hand, manual optimization of welding trajectory is very difficult and hard to get this under automatic control. For this reason, in the process of welding robot manipulator repeatedly perform the same tasks, how to find a more efficient, less costly, and even the optimal trajectory through smart algorithms is the key point in the field of intelligent control of welding robot.
In this thesis, the chip welding trajectory of manipulator was optimised from both the system energy and time. In the aspect of system energy, the Denavit-Hartenberg theory was used to achieve joint coordinates and Cartesian coordinate transformation, establish the motion equations, so to obtain effective self-learning capabilities of welding robot manipulator trajectory planning by setting some rules to meet the industry needs. In the aspect of time optimization, through the research of chip solder joints' distribution, the problem was transformed to the Hamilton circuit problem, improved genetic algorithm was used to obtaind optimal Hamilton circuit, so to optimise manipulator's welding trajectory. The effectiveness of improved genetic algorithm in the practical application of manipulator's chip welding was proved by the result of experiments.
引文
[1]张培艳.工业机器人操作与应用实践教程.上海-上海交通大学出版社.
[2]韩建海.工业机器人.武汉-华中科技大学出版社2009.
[3]赵景山.冯之敬.楮福磊.机器人机构自由度分析理论.北京-科技出版社2009.
[4]YueHai Wang, Ning Chi.Intelligent Control System of Trajectory Planning for a Welding Robot.2011 3rd International Conference on Computer and Automation Engineering.
[5]陈亮.焊接机器人路径规划问题的算法研究[D].武汉科技大学,2010.
[6]Zhenyu Liu, Wanghui Bu, Jianrong Tan Motion navigation for arc welding robots based on feature mapping in a simulation environment A pr.2010 Robotics and Computer-Integrated Manufacturing.
[7]Min-jae Oh, Sang-Moo Lee,Tae-wan Kim, Kyu-Yeul Lee, Jongwon Kim Design of a teaching pendant program for a mobile shipbuilding welding robot using a PDA Mar 2010 Computer-Aided Design.
[8]费向海.焊接机器人轨迹规划[D].辽宁工学院,2007.
[9]赵敏.胡中华.一种求解机器入路径规划的智能优化算法,2009年
[10]Donghun Lee, Namkug Ku,Tae-Wan Kim, Jongwon Kim,Kyu-Yeul Lee,Youg-Shuk Son Development and application of an intelligent welding robot system for shipbuilding Apr.2011 Robotics and Computer-Integrated Manufacturing.
[11]Bin Niu,Yonglin Chi,Hui Zhang Dynamic electrode force control of resistance spot welding robot Dec.2009 Proceedings of the 2009 international conference on Robotics and biomimetics
[12]Theodore P. Pachidis, Kostas N. Tarchanidis, John N. Lygouras, Philippos G Tsalides Robot path generation method for a welding system based on pseudo stereo visual servo control Jan.2005 EURASIP Journal on Applied Signal Processing
[13]倪厚强.陈建新.张志高等.基于混合遗传算法的机器人操作臂最优路径规划[J].机械设计,2008,(12).
[14]勾治践,孙影,徐连香等.六自由度点焊机器人运动学仿真[J].机械制造与自动化,2009,(02).
[15]李擎.张伟.尹怡欣等.一种用于最优路径规划的改进遗传算法[J].信息与控制,2006,(04).
[16]李玲.六自由度机器人运动学三维图形仿真研究[D].大连海事大学,2008.
[17]李天友,孟正大,赵娇娇等.基于焊接机器人的关节空间轨迹规划方法[J].电焊机,2009,(04).
[18]李东洁,邱江艳,尤波.一种机器人轨迹规划的优化算法[J].电机与控制学报,2009,(01).
[19]张忠奎.关节型机器人设计平台的开发及轨迹规划算法研究[D].山东理工大学,2010.
[20](美)Mahesh Chand著韩江译.GDI+图形程序设计.北京-电子工业出版社2005.
[21]贺淑娟.六自由度机械臂路径规划的分析与设计.东北大学,2008.
[22]马强.六自由度机械臂轨迹规划研究[D].哈尔滨工程大学,2007.
[23]赵显阳.白车身装焊夹具的设计及点焊机器人的焊接仿真[D].电子科技大学,2007.
[24]田西勇.机器人轨迹规划方法研究[D].北京邮电大学.2008.
[25]颜世周.一种六自由度机器人的开发与轨迹规划算法研究[D].山东理工大学,2009.
[26]Wang Yigang,Cui Jialin, Fan Shengli A Quick Algorithm to Track Welding Line Based on Computer Vision Dec.2009 Proceedings of the 2009 Second International Symposium on Computational Intelligence and Design
[27]李玮.关于旅行商问题的改进遗传算法[D].重庆大学.2004.
[28]王娜.求解TSP的改进遗传算法[D].西安电子科技大学,2010.
[29]明亮.遗传算法的模式理论及收敛理论[D].西安电子科技大学,2006.
[30]Donghun Lee, Namkug Ku,Tae-Wan Kim,Jongwon Kim,Kyu-Yeul Lee,Youg-Shuk Son Development and application of an intelligent welding robot system for shipbuilding Apr.2011 Robotics and Computer-Integrated Manufacturing.
[31]张晓辉.焊接机器人控制系统的研究与设计[D].东华大学.2010.
[32]王彬.中国焊接生产机械化自动化技术发展回顾[J].焊接技术.2000.(03).
[33]张颜峰.自动化焊接机器人生产线优化研究.上海交通大学2010.
[2]韩建海.工业机器人.武汉-华中科技大学出版社2009.
[3]赵景山.冯之敬.楮福磊.机器人机构自由度分析理论.北京-科技出版社2009.
[4]YueHai Wang, Ning Chi.Intelligent Control System of Trajectory Planning for a Welding Robot.2011 3rd International Conference on Computer and Automation Engineering.
[5]陈亮.焊接机器人路径规划问题的算法研究[D].武汉科技大学,2010.
[6]Zhenyu Liu, Wanghui Bu, Jianrong Tan Motion navigation for arc welding robots based on feature mapping in a simulation environment A pr.2010 Robotics and Computer-Integrated Manufacturing.
[7]Min-jae Oh, Sang-Moo Lee,Tae-wan Kim, Kyu-Yeul Lee, Jongwon Kim Design of a teaching pendant program for a mobile shipbuilding welding robot using a PDA Mar 2010 Computer-Aided Design.
[8]费向海.焊接机器人轨迹规划[D].辽宁工学院,2007.
[9]赵敏.胡中华.一种求解机器入路径规划的智能优化算法,2009年
[10]Donghun Lee, Namkug Ku,Tae-Wan Kim, Jongwon Kim,Kyu-Yeul Lee,Youg-Shuk Son Development and application of an intelligent welding robot system for shipbuilding Apr.2011 Robotics and Computer-Integrated Manufacturing.
[11]Bin Niu,Yonglin Chi,Hui Zhang Dynamic electrode force control of resistance spot welding robot Dec.2009 Proceedings of the 2009 international conference on Robotics and biomimetics
[12]Theodore P. Pachidis, Kostas N. Tarchanidis, John N. Lygouras, Philippos G Tsalides Robot path generation method for a welding system based on pseudo stereo visual servo control Jan.2005 EURASIP Journal on Applied Signal Processing
[13]倪厚强.陈建新.张志高等.基于混合遗传算法的机器人操作臂最优路径规划[J].机械设计,2008,(12).
[14]勾治践,孙影,徐连香等.六自由度点焊机器人运动学仿真[J].机械制造与自动化,2009,(02).
[15]李擎.张伟.尹怡欣等.一种用于最优路径规划的改进遗传算法[J].信息与控制,2006,(04).
[16]李玲.六自由度机器人运动学三维图形仿真研究[D].大连海事大学,2008.
[17]李天友,孟正大,赵娇娇等.基于焊接机器人的关节空间轨迹规划方法[J].电焊机,2009,(04).
[18]李东洁,邱江艳,尤波.一种机器人轨迹规划的优化算法[J].电机与控制学报,2009,(01).
[19]张忠奎.关节型机器人设计平台的开发及轨迹规划算法研究[D].山东理工大学,2010.
[20](美)Mahesh Chand著韩江译.GDI+图形程序设计.北京-电子工业出版社2005.
[21]贺淑娟.六自由度机械臂路径规划的分析与设计.东北大学,2008.
[22]马强.六自由度机械臂轨迹规划研究[D].哈尔滨工程大学,2007.
[23]赵显阳.白车身装焊夹具的设计及点焊机器人的焊接仿真[D].电子科技大学,2007.
[24]田西勇.机器人轨迹规划方法研究[D].北京邮电大学.2008.
[25]颜世周.一种六自由度机器人的开发与轨迹规划算法研究[D].山东理工大学,2009.
[26]Wang Yigang,Cui Jialin, Fan Shengli A Quick Algorithm to Track Welding Line Based on Computer Vision Dec.2009 Proceedings of the 2009 Second International Symposium on Computational Intelligence and Design
[27]李玮.关于旅行商问题的改进遗传算法[D].重庆大学.2004.
[28]王娜.求解TSP的改进遗传算法[D].西安电子科技大学,2010.
[29]明亮.遗传算法的模式理论及收敛理论[D].西安电子科技大学,2006.
[30]Donghun Lee, Namkug Ku,Tae-Wan Kim,Jongwon Kim,Kyu-Yeul Lee,Youg-Shuk Son Development and application of an intelligent welding robot system for shipbuilding Apr.2011 Robotics and Computer-Integrated Manufacturing.
[31]张晓辉.焊接机器人控制系统的研究与设计[D].东华大学.2010.
[32]王彬.中国焊接生产机械化自动化技术发展回顾[J].焊接技术.2000.(03).
[33]张颜峰.自动化焊接机器人生产线优化研究.上海交通大学2010.